Cognitive, behavioral, and psychological manifestations of COVID-19 in post-acute rehabilitation setting: preliminary data of an observational study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Psychological, emotional, and behavioral domains could be altered in COVID-19 patients and measurement of variables within these domains seems to be mandatory. Neuropsychological assessment could detect possible cognitive impairment caused by COVID-19 and the choice of appropriate tools is an important question. Aim of this exploratory study was to verify the effectiveness of an assessment model for patients with COVID-19. Twelve patients were enrolled and tested with Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Anxiety and Depression Short Scale (AD-R), and the Neuropsychiatry Inventory (NPI), at the time of their entrance (T0) and discharge (T1) from a rehabilitative unit. Moreover, a follow-up evaluation after 3 months (T2) has been conducted on eight patients. Results showed that at baseline (T0), 58.3% of the patients reported a score below cut-off at MMSE and 50% at MoCA. Although a significant amelioration was found only in NPI scores, a qualitative improvement has been detected at all tests, except for MoCA scores, in the T0-T1 trend analysis. A one-way repeated measures analysis of variance showed a significant variation in AD-R depression score, considering the three-assessment time (T0, T1, and T2). The evaluation and tracking over time of the impact of COVID-19 on cognitive, psychological, and behavioral domains has relevant implications for rehabilitation and long-term assistance needs planning. The choice of assessment tools should consider patients vulnerability and match the best compromise among briefness, sensitivity, and specificity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it